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Received: 2 November 2016 Revised: 19 February 2017 Accepted: 21 February 2017 DOI: 10.1002/ece3.2923
ORIGINAL RESEARCH
Maximum thermal tolerance trades off with chronic tolerance of high temperature in contrasting thermal populations of Radix balthica Magnus P. Johansson | Anssi Laurila Animal Ecology/Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden Correspondence Anssi Laurila, Animal Ecology/Department of Ecology and Genetics, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden. Email:
[email protected] Funding information Swedish Research Council, Grant/Award Number: 621-2010-5435; Stiftelsen för Zoologisk Forskning
Abstract Thermal adaptation theory predicts that thermal specialists evolve in environments with low temporal and high spatial thermal variation, whereas thermal generalists are favored in environments with high temporal and low spatial variation. The thermal environment of many organisms is predicted to change with globally increasing temperatures and thermal specialists are presumably at higher risk than thermal generalists. Here we investigated critical thermal maximum (CTmax) and preferred temperature (Tp) in populations of the common pond snail (Radix balthica) originating from a small- scale system of geothermal springs in northern Iceland, where stable cold (ca. 7°C) and warm (ca. 23°C) habitats are connected with habitats following the seasonal thermal variation. Irrespective of thermal origin, we found a common Tp for all populations, corresponding to the common temperature optimum (Topt) for fitness-related traits in these populations. Warm-origin snails had lowest CTmax. As our previous studies have found higher chronic temperature tolerance in the warm populations, we suggest that there is a trade-off between high temperature tolerance and performance in other fitness components, including tolerance to chronic thermal stress. Tp and CTmax were positively correlated in warm-origin snails, suggesting a need to maintain a minimum “warming tolerance” (difference in CTmax and habitat temperature) in warm environments. Our results highlight the importance of high mean temperature in shaping thermal performance curves. KEYWORDS
acute thermal stress, chronic thermal stress, critical thermal maximum, gastropods, gene flow, geothermal spring, Lake Mývatn, preferred temperature, thermal adaptation
1 | INTRODUCTION
example, tropical ectotherms have been postulated to have a higher risk of extinction due to climate warming as they are more likely to
Temperature is a ubiquitous force influencing most biological pro-
have evolved as thermal specialists, increasing their sensitivity to fluc-
cesses in nature (Angilletta, 2009; Kingsolver & Huey, 2008). With
tuations in temperature (Deutsch et al., 2008; Tewksbury, Huey, &
globally increasing temperatures (IPCC, 2013), the need to under-
Deutsch, 2008; but see Walters, Blanckenhorn, & Berger, 2012).
stand thermal performance and how organisms can adapt to changing
Thermal sensitivity can be presented as a thermal performance
temperature regimes has become more urgent (Angilletta, 2009). For
curve (TPC): a usually a left-skewed Gaussian distribution limited by
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2017 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Ecology and Evolution. 2017;1–8.
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critical minimum (CTmin) and maximum (CTmax) temperatures (Angilletta,
(de Mazancourt, Johnson, & Barraclough, 2008). In order to better
2009; Huey & Kingsolver, 1989). CTmax allows estimation of an organ-
understand how thermal adaptation is affected by the combined ef-
isms’ “warming tolerance”, defined as the difference between CTmax
fects of gene flow and natural selection, studies of systems allowing
and average temperature of the natural habitat (Thab; Deutsch et al.,
gene exchange over shorter distances are needed (Keller, Alexander,
2008). The performance is maximized at optimal temperature (Topt),
Holderegger, & Edwards, 2013; Logan, Dureya, Molnar, Kessler, &
which is of high interest when the trait is fitness-related and puta-
Calsbeek, 2016; Merilä & Hendry, 2014; Richter-Boix et al., 2015).
tively under selection. In addition, Topt is used to estimate the “thermal
Here we investigated thermal preference (Tp) and maximum tem-
safety margin” (TSM; defined as the difference between Topt and Thab).
perature tolerance (CTmax) in the common pond snail Radix balth-
However, as different traits often have different Topt, estimating an
ica originating from three contrasting thermal environments within
overall Topt can be difficult (Angilletta, 2009; Huey & Stevenson, 1979;
Lake Mývatn, northern Iceland. In Lake Mývatn, geothermally heated
Martin & Huey, 2008). As ectotherms use thermoregulatory behavior
groundwater creates a system of cold (ca. 7°C) and warm (ca. 23°C)
as a mean to maximize their performance (Grant & Dunham, 1988;
springs along the shore line (Figure 1). While temperature variation
Martin & Huey, 2008), the preferred temperature (Tp) is often used as
close to the springs is low, these habitats are connected by areas with
a proxy for the overall Topt (Angilletta, 2009). Thermal performance evolves in response to variation in thermal
seasonal temperature variation (Figure 1). Genetic studies show that populations in similar thermal habitats are significantly differentiated in
regimes (Angilletta, 2009). For example, studies over larger geographic
neutral molecular markers, but they are more similar in markers puta-
scales have shown that both CTmax and CTmin decrease with increas-
tively under selection (Johansson, Quintela, & Laurila, 2016; Quintela,
ing latitude (Addo-Bediako, Chown, & Gaston, 2000; Sunday, Bates,
Johansson, Kristjansson, Barreiro, & Laurila, 2014). Yet these very
& Dulvy, 2011), but CTmax appears to be evolutionarily more rigid
contrasting thermal environments are connected by low gene flow
than CTmin (Araújo et al., 2013). However, thermal tolerance can be
(Johansson, Quintela, et al., 2016; Quintela et al., 2014). Hence, Lake
affected by both intensity and duration of a thermal stress. Recently,
Mývatn constitutes an ideal system to evaluate the evolution of Tp and
Rezende, Casteneda, and Santos (2014) suggested that there may be a
CTmax in the presence of potentially disrupting evolutionary forces.
trade-off between acute and chronic tolerance of high temperatures.
As a small aquatic ectotherm with low mobility, R. balthica is a poor
This trade-off may explain the counter-intuitive results where warm-
thermoregulator with body temperature equalling the surrounding en-
origin populations have lower CTmax than cold-origin populations (e.g.,
vironment (Reynolds & Casterlin, 1979). Although snails in the close
Castañeda, Rezente, & Santos, 2015; Sgrò et al., 2010). A common assumption in optimality models of thermal adaptation
vicinity of the geothermal springs can be expected to show a higher degree of thermal specialization than snails in habitats subjected to
(e.g., Gilchrist, 1995; Lynch & Gabriel, 1987) is that there is a close
seasonal temperature variation (Ghalambor et al., 2006; Janzen, 1967),
match between an organism’s Tp and Topt (Angilletta, 2009). However,
laboratory and field experiments showed that life history patterns
in organisms that are poor thermoregulators, Tp should be lower than
were better explained by cogradient variation (Conover, Duffy, & Hice,
Topt (Martin & Huey, 2008). This is also true in situations when locally
2009) with warm-origin snails have higher growth and reproduction
adapted individuals from contrasting environments differ in their per-
in all temperatures (Johansson, Ermold, Kristjansson, & Laurila, 2016).
formance (Asbury & Angilletta, 2010). Such differences could arise
However, snails from all habitats had roughly similar Topt for growth
when there are differences in food availability or when maximum
and reproduction (Johansson, Ermold, et al., 2016). As these two traits
performance increases with optimum temperature (i.e., “Hotter is bet-
are important fitness components, we expect to find a common Tp ir-
ter”; Bennett, 1987; Kingsolver & Huey, 2008; Angilletta, 2009). Any
respective of thermal origin. An alternative prediction is that seasonal
mismatch between Tp and Topt is predicted to increase with tempera-
origin snails have a lower Tp than either cold or warm-origin snails due
ture variation within generations (Asbury & Angilletta, 2010; Lynch &
to the higher variation in environmental temperature requiring a larger
Gabriel, 1987). Alternatively, although thermal specialists generally
overall TSM. Previous common garden and reciprocal transplant ex-
evolve in environments with low temperature variation (Ghalambor,
periments showed that warm-origin snails had higher survival in high
Huey, Martin, Tewksbury, & Wang, 2006; Janzen, 1967), they are ex-
temperatures (Johansson, Ermold, et al., 2016). Consequently, we ex-
pected to show a larger difference between Tp and Topt than thermal
pect to find the highest CTmax in warm-origin populations and that
generalists, because the increased asymmetry of the TPC increases
seasonal origin snails are more similar to cold origin snails, as seasonal
their sensitivity to temperature fluctuations (Martin & Huey, 2008).
habitats have temperatures closer to those experienced in the tempo-
Importantly, while studies on thermal performance over larger geo-
rally stable cold sites. Alternatively, if acute thermal stress tolerance
graphic gradients (reviewed by e.g., Addo-Bediako et al., 2000; Araújo
trades off with chronic stress tolerance (Rezende et al., 2014), we ex-
et al., 2013; Sunday et al., 2011) have increased our understanding
pect that warm-origin snails have lowest CTmax.
of large-scale effects of climatic variation and warming, they are less helpful in understanding how closely located populations will evolve in response to local variation in temperatures. Specifically, gene flow
2 | METHODS
can have a strong effect on local adaptation over short spatial distances (Kawecki & Ebert, 2004; Räsänen & Hendry, 2008; Sultan &
Radix balthica is a pulmonate snail common in freshwaters throughout
Spencer, 2002) and influence how populations adapt to climate change
northern Europe (Lakowitz, Brönmark, & Nyström, 2008; Pfenninger,
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F I G U R E 1 Map of Lake Mývatn and the locations of the sampled thermal habitats. The figures indicate temperature measurements from the three thermal environment types during May 18 and September 18, 2011 (above) and 2012 (below). Cold, seasonal, and warm are drawn with solid, dotted, and dashed lines, respectively
Salinger, Haun, & Feldmeyer, 2011) and the most common gastropod
every fourth hour. Temperature is reported as the average from three
in Lake Mývatn. Although it has direct development, it is often con-
temperature loggers placed at the bottom at 50 cm depth at each
sidered an early colonizer mainly relying on bird-assisted dispersal
site. Two of the six sites selected for this study (Figure 1) were sub-
(Haun, Salinger, Pachzelt, & Pfenninger, 2012; Lakowitz et al., 2008;
jected to seasonal temperature variation (mean °C ± SE, Seasonal 1:
Pfenninger et al., 2011).
8.59 ± 0.06, Seasonal 2: 9.13 ± 0.07) and the remaining four were
Lake Mývatn (65°60′N, 17°00′W; Figure 1) was formed in a lava eruption ca. 2,300 years ago (Einarsson et al., 2004). It is fed by
classified as either temporally stable cold (Cold 1: 6.39 ± 0.02, Cold 2: 7.52 ± 0.02) or warm (Warm 1: 22.96 ± 0.04, Warm 2: 22.20 ± 0.03).
ground water that passes through differently heated volcanic bedrock,
We collected 100–150 juvenile R. balthica (shell length 5–8 mm) at
forming cold springs in the south-eastern part of the lake and warm
each of the six sites in June 2011 (Figure 1). Previous studies showed
springs in the north-eastern part (Einarsson et al., 2004; Ólafsson,
that snails in all these sites (henceforth populations) were significantly
1979). Temperature close to the springs is relatively stable over time,
genetically differentiated from each other (even within a thermal
although small temperature fluctuations occur due to variation in geo-
habitat-type) in neutral AFLP-markers (Johansson, Quintela, et al.,
thermal activity (Ólafsson, 1979; Figure 1). The area affected by the
2016). The snails were transported to Uppsala University where they
springs is extensive as indicated by the fact that a large proportion
were maintained in a walk-in climate-controlled room at 12°C with
of the eastern shore of Lake Mývatn remains ice-free during winter
a 16 hr light:8 hr dark regime. Each population was kept in multiple
(Ólafsson, 1979). Field measurements of temperature were taken be-
35 × 25 × 25 cm plastic aquaria filled with 15 L of reconstituted soft
tween early May and late September 2011 and 2012 with iButton®
water (RSW; APHA, 1985). The snails were allowed to reproduce freely
DS1921G temperature loggers programmed to record temperature
within each aquarium and all egg batches were collected and placed in
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JOHANSSON and LAURILA
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new aquaria. The experiments were conducted on the F1 generation.
(2010). Individual preferred temperatures were analyzed with an
Importantly, as the experiments were conducted on the first labora-
ANOVA using thermal origin as a factor. Sites within thermal origin
tory generation, we cannot exclude the possibility that our results are
were pooled as there were no differences in Tp between sites (t tests,
influenced by cross-generational effects (Räsänen & Kruuk, 2007). A
p > .38). Snail size (shell length) was not correlated with Tp (r117 = −.05,
common garden experiment conducted on laboratory reared F3 snails
p = .58).
estimated a common Topt at 20°C for growth rate and at 16°C for re-
Differences in CTmax between thermal origins were analyzed with
production (Johansson, Ermold, et al., 2016). We used the first tem-
an ANOVA with site pooled within thermal origin (t tests, p > .14).
perature as a measure of Topt throughout the manuscript as growth has
Pearson correlations between CTmax and Tp were calculated both over
a major influence on ectotherm life history and size is a good predictor
all thermal origins and within each thermal origin. Only snails that had
of fecundity in pulmonates (Dillon, 2010; Kingsolver & Huey, 2008).
recovered 24 hr after losing attachment were included in the analyses on CTmax; however, the results did not change qualitatively when all
2.1 | Preferred temperature (Tp)
snails were included. In addition to CTmax, we estimated the temperature at which half of the snails remained attached (CT50) for each ther-
In order to create an experimental temperature gradient, ten
mal origin. This was made by fitting a curve with the R-function “loess”
500 × 20 × 20 mm channels separated by 2 mm were milled in a single
to the data points representing the percentage of attached snails at
block of aluminium. Each channel was filled with 125 ml RSW. The block
each temperature.
was positioned so that one end rested on a warming plate and the other end on a cooling plate, creating a temperature gradient with a difference of 24°C (min: 1 ± 0.5°C, max: 25 ± 1°C). The temperature gradient
3 | RESULTS
was stable between trials (adj-R2 = 0.95) with an average temperature increase of 0.36°C/cm. Twenty snails (average shell length 7.4 ± 0.9
The preferred temperature was different from a random distribution
[SE] mm) were randomly selected from each site and placed individu-
in all thermal origins (Cold: t38 = 7.51, p
